Atrial fibrillation (AF) is one of most common cardiac rhythm disorders and irregularities of cardiac patients. Usually, surface ECG signal analysis based on waveform morphology and time domain parameters is utilized for cardiac arrhythmia detection by P wave signal characterization, for example. Known invasive catheter based ablation is used for treating and terminating atrial functional arrhythmias and electrophysiological disorders, especially atrial fibrillation and flutters. However, known clinical ablation and treatment procedures are based on physician subjective estimation and require extensive clinical knowledge and electrophysiological experience. There is a lack of an efficient and effective ablation control system for ablation parameter setting and adjustment, such as for control of duration of ablation shock signals, ablation energy, ablation pulse pattern and ablation site priority. There is also a lack of a system providing qualitative and quantitative characterization of atrial fibrillation, especially for quantification of severity of AF.
Usually, surface ECG signal analysis based on waveform morphology and time domain parameters is utilized for cardiac AF rhythm detection and characterization. Such waveform morphology includes P wave morphology changes, R-R wave time interval, and heart rate variability. However, known waveform morphology and time domain parameter analysis is often subjective and time-consuming, and requires extensive expertise and clinical experience for accurate pathology interpretation and proper cardiac rhythm management. Some known recent research has applied mathematical theories to biomedical signal interpretation, such as, frequency analysis (such as dominant frequency analysis), wavelet decomposition analysis, statistical analysis (such as autocorrelation analysis, coherence analysis), and nonlinear entropy evaluation. Nevertheless, this research is focused on generating a pathology index for qualitative cardiac AF rhythm identification. Know methods for atrial pathology and malfunction diagnosis and interpretation typically focus on qualitative electrical pulse conduction and excitation progression in an atrial chamber and tissue. There is a lack of a system able to identify atrial arrhythmia area size and severity for ablation treatment quantitatively, such as for an atrial fibrillation site in the right and left atrial chambers.
Known systems track and navigate atrial chamber size, myocardial wall thickness, tissue electrical impedance and atrial contraction mode but fail to comprehensively determine atrial arrhythmia treatment including ablation energy and pulse pattern selection. Known ablation machines and electrical treatment medical devices utilize continuous ablation shock signals for burning and terminating abnormal tissue function, such as pathological atrial fibrillation rotors in atrial chamber tissue but fail to comprehensively modulate ablation energy pulses by adaptively adjusting ablation parameters during electrical treatment including electrical pulse length, energy and ablation time length. A system according to invention principles addresses these deficiencies and associated problems.